{"title":"全球磁共振成像数据库的现状,重点关注精神和神经疾病。","authors":"Saori C Tanaka, Kiyoto Kasai, Yasumasa Okamoto, Shinsuke Koike, Takuya Hayashi, Ayumu Yamashita, Okito Yamashita, Tom Johnstone, Franco Pestilli, Kenji Doya, Go Okada, Hotaka Shinzato, Eri Itai, Yuji Takahara, Akihiro Takamiya, Motoaki Nakamura, Takashi Itahashi, Ryuta Aoki, Yukiaki Koizumi, Masaaki Shimizu, Jun Miyata, Shuraku Son, Morio Aki, Naohiro Okada, Susumu Morita, Nobukatsu Sawamoto, Mitsunari Abe, Yuki Oi, Kazuaki Sajima, Koji Kamagata, Masakazu Hirose, Yohei Aoshima, Sayo Hamatani, Nobuhiro Nohara, Misako Funaba, Tomomi Noda, Kana Inoue, Jinichi Hirano, Masaru Mimura, Hidehiko Takahashi, Nobutaka Hattori, Atsushi Sekiguchi, Mitsuo Kawato, Takashi Hanakawa","doi":"10.1111/pcn.13717","DOIUrl":null,"url":null,"abstract":"<p><p>Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.</p>","PeriodicalId":20938,"journal":{"name":"Psychiatry and Clinical Neurosciences","volume":" ","pages":"563-579"},"PeriodicalIF":5.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The status of MRI databases across the world focused on psychiatric and neurological disorders.\",\"authors\":\"Saori C Tanaka, Kiyoto Kasai, Yasumasa Okamoto, Shinsuke Koike, Takuya Hayashi, Ayumu Yamashita, Okito Yamashita, Tom Johnstone, Franco Pestilli, Kenji Doya, Go Okada, Hotaka Shinzato, Eri Itai, Yuji Takahara, Akihiro Takamiya, Motoaki Nakamura, Takashi Itahashi, Ryuta Aoki, Yukiaki Koizumi, Masaaki Shimizu, Jun Miyata, Shuraku Son, Morio Aki, Naohiro Okada, Susumu Morita, Nobukatsu Sawamoto, Mitsunari Abe, Yuki Oi, Kazuaki Sajima, Koji Kamagata, Masakazu Hirose, Yohei Aoshima, Sayo Hamatani, Nobuhiro Nohara, Misako Funaba, Tomomi Noda, Kana Inoue, Jinichi Hirano, Masaru Mimura, Hidehiko Takahashi, Nobutaka Hattori, Atsushi Sekiguchi, Mitsuo Kawato, Takashi Hanakawa\",\"doi\":\"10.1111/pcn.13717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.</p>\",\"PeriodicalId\":20938,\"journal\":{\"name\":\"Psychiatry and Clinical Neurosciences\",\"volume\":\" \",\"pages\":\"563-579\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychiatry and Clinical Neurosciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/pcn.13717\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/20 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychiatry and Clinical Neurosciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/pcn.13717","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/20 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
The status of MRI databases across the world focused on psychiatric and neurological disorders.
Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.
期刊介绍:
PCN (Psychiatry and Clinical Neurosciences)
Publication Frequency:
Published 12 online issues a year by JSPN
Content Categories:
Review Articles
Regular Articles
Letters to the Editor
Peer Review Process:
All manuscripts undergo peer review by anonymous reviewers, an Editorial Board Member, and the Editor
Publication Criteria:
Manuscripts are accepted based on quality, originality, and significance to the readership
Authors must confirm that the manuscript has not been published or submitted elsewhere and has been approved by each author